Extracting the information of angle and axis - c++

Question

Here I got the code of extracting the orientation of the object in the image. I am new to OpenCV and C++. But I need to get this work done.
My question is, how to extract, write out the information of the angle and axis in this code?
#include "pch.h"
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
using namespace std;
using namespace cv;
// Function declarations
void drawAxis(Mat&, Point, Point, Scalar, const float);
double getOrientation(const vector<Point> &, Mat&);
void drawAxis(Mat& img, Point p, Point q, Scalar colour, const float scale = 0.2)
{
double angle = atan2((double)p.y - q.y, (double)p.x - q.x); // angle in radians
double hypotenuse = sqrt((double)(p.y - q.y) * (p.y - q.y) + (p.x - q.x) * (p.x - q.x));
// Here we lengthen the arrow by a factor of scale
q.x = (int)(p.x - scale * hypotenuse * cos(angle));
q.y = (int)(p.y - scale * hypotenuse * sin(angle));
line(img, p, q, colour, 1, LINE_AA);
// create the arrow hooks
p.x = (int)(q.x + 9 * cos(angle + CV_PI / 4));
p.y = (int)(q.y + 9 * sin(angle + CV_PI / 4));
line(img, p, q, colour, 1, LINE_AA);
p.x = (int)(q.x + 9 * cos(angle - CV_PI / 4));
p.y = (int)(q.y + 9 * sin(angle - CV_PI / 4));
line(img, p, q, colour, 1, LINE_AA);
}
double getOrientation(const vector<Point> &pts, Mat &img)
{
//Construct a buffer used by the pca analysis
int sz = static_cast<int>(pts.size());
Mat data_pts = Mat(sz, 2, CV_64F);
for (int i = 0; i < data_pts.rows; i++)
{
data_pts.at<double>(i, 0) = pts[i].x;
data_pts.at<double>(i, 1) = pts[i].y;
}
//Perform PCA analysis
PCA pca_analysis(data_pts, Mat(), PCA::DATA_AS_ROW);
//Store the center of the object
Point cntr = Point(static_cast<int>(pca_analysis.mean.at<double>(0, 0)),
static_cast<int>(pca_analysis.mean.at<double>(0, 1)));
//Store the eigenvalues and eigenvectors
vector<Point2d> eigen_vecs(2);
vector<double> eigen_val(2);
for (int i = 0; i < 2; i++)
{
eigen_vecs[i] = Point2d(pca_analysis.eigenvectors.at<double>(i, 0),
pca_analysis.eigenvectors.at<double>(i, 1));
eigen_val[i] = pca_analysis.eigenvalues.at<double>(i);
}
// Draw the principal components
circle(img, cntr, 3, Scalar(255, 0, 255), 2);
Point p1 = cntr + 0.02 * Point(static_cast<int>(eigen_vecs[0].x * eigen_val[0]), static_cast<int>(eigen_vecs[0].y * eigen_val[0]));
Point p2 = cntr - 0.02 * Point(static_cast<int>(eigen_vecs[1].x * eigen_val[1]), static_cast<int>(eigen_vecs[1].y * eigen_val[1]));
drawAxis(img, cntr, p1, Scalar(0, 255, 0), 1);
drawAxis(img, cntr, p2, Scalar(255, 255, 0), 5);
double angle = atan2(eigen_vecs[0].y, eigen_vecs[0].x); // orientation in radians
return angle;
}
int main(int argc, char** argv)
{
// Load image
CommandLineParser parser(argc, argv, "{#input | joint2.bmp | input image}");
parser.about("This program demonstrates how to use OpenCV PCA to extract the orientation of an object.\n");
parser.printMessage();
Mat src = imread(parser.get<String>("#input"));
// Check if image is loaded successfully
if (src.empty())
{
cout << "Problem loading image!!!" << endl;
return EXIT_FAILURE;
}
imshow("src", src);
// Convert image to grayscale
Mat gray;
cvtColor(src, gray, COLOR_BGR2GRAY);
// Convert image to binary
Mat bw;
threshold(gray, bw, 200, 255, THRESH_BINARY | THRESH_OTSU);
// Find all the contours in the thresholded image
vector<vector<Point> > contours;
findContours(bw, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);
for (size_t i = 0; i < contours.size(); i++)
{
// Calculate the area of each contour
double area = contourArea(contours[i]);
// Ignore contours that are too small or too large
if (area < 1e2 || 1e5 < area) continue;
// Draw each contour only for visualisation purposes
drawContours(src, contours, static_cast<int>(i), Scalar(0, 0, 255), 2);
// Find the orientation of each shape
getOrientation(contours[i], src);
}
imshow("output", src);
waitKey();
return 0;
}
Here is the image of the object:
And here is the result:
As you see, it finds orientation correctly, but I need the information about the angle and which is which axis to be written.
Will be very grateful if someone knows how to do it!
EDIT: I have figured out how to find the information about the center, area, and the angle.
/// Get the moments
vector<Moments> mu(contours.size());
for (size_t i = 0; i < contours.size(); i++)
{
mu[i] = moments(contours[i]);
}
/// Get the mass centers
vector<Point2f> mc(contours.size());
for (size_t i = 0; i < contours.size(); i++)
{
//add 1e-5 to avoid division by zero
mc[i] = Point2f(static_cast<float>(mu[i].m10 / (mu[i].m00 + 1e-5)),
static_cast<float>(mu[i].m01 / (mu[i].m00 + 1e-5)));
}
imshow("output", src);
cout << "\t Info: Area and angle \n";
for (size_t i = 0; i < contours.size(); i++)
{
cout << " * Contour[" << i << "] - Center: "<< mc[i]
<< " - Area: " << contourArea(contours[i]) << " - Angle: " << getOrientation(contours[i],src)*180/CV_PI << endl;
}
But still don't know how to denote which arrow is which axis in the image.

Answer 1

So I have figured out everything I need (almost).
Here is the final code:
#include "pch.h"
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
using namespace std;
using namespace cv;
// Function declarations
void drawAxis(Mat&, Point, Point, Scalar, const float);
double getOrientation(const vector<Point> &, Mat&);
string s = "";
void drawAxis(Mat& img, Point p, Point q, Scalar colour, const float scale = 0.2)
{
double angle = atan2((double)p.y - q.y, (double)p.x - q.x); // angle in radians
double hypotenuse = sqrt((double)(p.y - q.y) * (p.y - q.y) + (p.x - q.x) * (p.x - q.x));
// Here we lengthen the arrow by a factor of scale
q.x = (int)(p.x - scale * hypotenuse * cos(angle));
q.y = (int)(p.y - scale * hypotenuse * sin(angle));
line(img, p, q, colour, 1, LINE_AA);
// create the arrow hooks
p.x = (int)(q.x + 9 * cos(angle + CV_PI / 4));
p.y = (int)(q.y + 9 * sin(angle + CV_PI / 4));
line(img, p, q, colour, 1, LINE_AA);
p.x = (int)(q.x + 9 * cos(angle - CV_PI / 4));
p.y = (int)(q.y + 9 * sin(angle - CV_PI / 4));
line(img, p, q, colour, 1, LINE_AA);
}
double getOrientation(const vector<Point> &pts, Mat &img)
{
//Construct a buffer used by the pca analysis
int sz = static_cast<int>(pts.size());
Mat data_pts = Mat(sz, 2, CV_64F);
for (int i = 0; i < data_pts.rows; i++)
{
data_pts.at<double>(i, 0) = pts[i].x;
data_pts.at<double>(i, 1) = pts[i].y;
}
//Perform PCA analysis
PCA pca_analysis(data_pts, Mat(), PCA::DATA_AS_ROW);
//Store the center of the object
Point cntr = Point(static_cast<int>(pca_analysis.mean.at<double>(0, 0)),
static_cast<int>(pca_analysis.mean.at<double>(0, 1)));
//Store the eigenvalues and eigenvectors
vector<Point2d> eigen_vecs(2);
vector<double> eigen_val(2);
for (int i = 0; i < 2; i++)
{
eigen_vecs[i] = Point2d(pca_analysis.eigenvectors.at<double>(i, 0),
pca_analysis.eigenvectors.at<double>(i, 1));
eigen_val[i] = pca_analysis.eigenvalues.at<double>(i);
}
// Draw the principal components
circle(img, cntr, 3, Scalar(255, 0, 255), 2);
Point p1 = cntr + 0.01 * Point(static_cast<int>(eigen_vecs[0].x * eigen_val[0]), static_cast<int>(eigen_vecs[0].y * eigen_val[0]));
Point p2 = cntr - 0.005 * Point(static_cast<int>(eigen_vecs[1].x * eigen_val[1]), static_cast<int>(eigen_vecs[1].y * eigen_val[1]));
drawAxis(img, cntr, p1, Scalar(0, 255, 0), 1);
putText(img, s = "Y-axis", p1, cv::FONT_HERSHEY_COMPLEX_SMALL, 1, cv::Scalar(255, 0, 100));
drawAxis(img, cntr, p2, Scalar(255, 255, 0), 5);
putText(img, s = "X-axis", p2/1.1 , cv::FONT_HERSHEY_COMPLEX_SMALL, 1, cv::Scalar(255, 0, 255));
double angle = atan2(eigen_vecs[0].y, eigen_vecs[0].x); // orientation in radians
return angle;
}
int main(int argc, char** argv)
{
// Load image
CommandLineParser parser(argc, argv, "{#input | circle3.bmp | input image}");
parser.about("This program demonstrates how to use OpenCV PCA to extract the orientation of an object.\n");
parser.printMessage();
Mat src = imread(parser.get<String>("#input"));
// Check if image is loaded successfully
if (src.empty())
{
cout << "Problem loading image!!!" << endl;
return EXIT_FAILURE;
}
imshow("src", src);
// Convert image to grayscale
Mat gray;
cvtColor(src, gray, COLOR_BGR2GRAY);
// Convert image to binary
Mat bw;
threshold(gray, bw, 70, 255, THRESH_BINARY | THRESH_OTSU);
// Find all the contours in the thresholded image
vector<vector<Point> > contours;
findContours(bw, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);
for (size_t i = 0; i < contours.size(); i++)
{
// Calculate the area of each contour
double area = contourArea(contours[i]);
// Ignore contours that are too small or too large
if (area < 1e2 || 1e5 < area) continue;
// Draw each contour only for visualisation purposes
drawContours(src, contours, static_cast<int>(i), Scalar(0, 0, 255), 2);
// Find the orientation of each shape
getOrientation(contours[i], src);
}
/// Get the moments
vector<Moments> mu(contours.size());
for (size_t i = 0; i < contours.size(); i++)
{
mu[i] = moments(contours[i]);
}
/// Get the mass centers
vector<Point2f> mc(contours.size());
for (size_t i = 0; i < contours.size(); i++)
{
//add 1e-5 to avoid division by zero
mc[i] = Point2f(static_cast<float>(mu[i].m10 / (mu[i].m00 + 1e-5)),
static_cast<float>(mu[i].m01 / (mu[i].m00 + 1e-5)));
for (int i = 0; i < contours.size(); i++) {
std::stringstream ss; ss << i;
putText(src, ss.str(), mc[i] + Point2f(10,-10), cv::FONT_HERSHEY_COMPLEX_SMALL, 1, cv::Scalar(255, 0, 255));
}
}
imshow("output", src);
cout << "\t Info: Area and angle \n";
for (size_t i = 0; i < contours.size(); i++)
{
cout << " * Contour[" << i << "] - Center: "<< mc[i]
<< " - Area: " << contourArea(contours[i]) << " - Angle X: " << getOrientation(contours[i],src)*180/CV_PI << endl;
}
waitKey();
return 0;
}
The only thing I want to know how to draw the coordinate system in the corner of the image. Because I don't understand the angle results.
The results of the final code: https://imgur.com/l7t9bns
And relevant information: https://imgur.com/OuE79rR